Factors Affecting the Use of Medical Articles for Citation and Academic Reference

Abstract

Introduction: Increases in publication quantity and the onset of open access have increased the complexity of conducting a literature search. Bibliometric markers, like impact factor (IF), have traditionally been used to help identify high-quality research. These markers exist amongst a variety of other factors, which poses the following question: what factors are examined when considering articles for clinical and academic research? Objective: To determine what factors are involved when authors choose citations to include in their publications. Methods: A voluntary and anonymous questionnaire-based survey was distributed to medical students, residents, and faculty from multiple medical schools across Canada during the 2020/2021 academic year. Survey ratings were scored on a 5-point Likert scale and open word response. Results: The study collected 156 complete sets of responses including 78 trainees (61 medical students and 17 residents), and 78 faculty. Language of the article (3.93) and availability on PubMed/Medline (3.77) were found more important than country of origin (2.14), institution (2.26), and IF (2.97). Trainees found the following factors more important than faculty: year of publication (3.94 vs 3.47, p = 0.0016), availability on Google/Google Scholar (2.51 vs 1.88, p = 0.0013), Open-access (2.46 vs 1.87, p = 0.0011), and Free access (2.73 vs 2.31, p = 0.049). Conclusion: Our study identified differences in faculty and trainee literature search preferences, bias towards English language publications, and the movement towards online literature sources. This knowledge provides insight into what biases individuals may be exposed to based on their language and literature search preferences. Future areas of research include how trainees’ opinions change over time, identifying trainee ability to recognize predatory journals, and the need for better online journal article translators to mitigate the language bias. We believe this will lead to higher quality evidence and optimal patient care amongst healthcare workers.